Intelligent learning algorithm and intelligent transportation-based energy management strategies for hybrid electric vehicles: A review
As one of the alternatives to conventional fuel vehicles, hybrid electric vehicles (HEV) offer
lower fuel consumption and fewer exhaust emissions. To improve the performance of the …
lower fuel consumption and fewer exhaust emissions. To improve the performance of the …
Uncertainties in onboard algorithms for autonomous vehicles: Challenges, mitigation, and perspectives
K Yang, X Tang, J Li, H Wang, G Zhong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Autonomous driving is considered one of the revolutionary technologies shaping humanity's
future mobility and quality of life. However, safety remains a critical hurdle in the way of …
future mobility and quality of life. However, safety remains a critical hurdle in the way of …
Prediction failure risk-aware decision-making for autonomous vehicles on signalized intersections
Motion prediction modules are crucial for autonomous vehicles to forecast the future
behavior of surrounding road users. Failures in prediction modules can mislead a …
behavior of surrounding road users. Failures in prediction modules can mislead a …
A Survey on an Emerging Safety Challenge for Autonomous Vehicles: Safety of the Intended Functionality
As the complexity of autonomous vehicles (AVs) continues to increase and artificial
intelligence algorithms are becoming increasingly ubiquitous, a novel safety concern known …
intelligence algorithms are becoming increasingly ubiquitous, a novel safety concern known …
Trustworthy autonomous driving via defense-aware robust reinforcement learning against worst-case observational perturbations
Despite the substantial advancements in reinforcement learning (RL) in recent years,
ensuring trustworthiness remains a formidable challenge when applying this technology to …
ensuring trustworthiness remains a formidable challenge when applying this technology to …
Uncertainty-aware decision-making for autonomous driving at uncontrolled intersections
Reinforcement learning (RL) has been widely used in the decision-making of autonomous
vehicles (AVs) in recent studies. However, existing RL methods generally find the optimal …
vehicles (AVs) in recent studies. However, existing RL methods generally find the optimal …
Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene
C Li, X Xu, H Zhu, J Gan, Z Chen, X Tang - Energy, 2024 - Elsevier
To address the comprehensive optimization problem of driving performance and fuel
economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in …
economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in …
Driving safety zone model oriented motion planning framework for autonomous truck platooning
A driving-safety-zone-model-oriented motion planning framework (DSZMF) is proposed for
autonomous platoons in heterogeneous driving environments with complex driving …
autonomous platoons in heterogeneous driving environments with complex driving …
Multi-lane eco-cruise for battery electric vehicles with terrain and traffic previews
The eco-cruise (EC) technique is recognized as an effective method to cut energy
consumption in battery electric vehicles (BEVs). Prior studies have examined the road slope …
consumption in battery electric vehicles (BEVs). Prior studies have examined the road slope …
AERO: Automotive ethernet real-time observer for anomaly detection in in-vehicle networks
Automotive Ethernet enables high-bandwidth in-vehicle networking, facilitating the
transmission of sensor data among electronic control units. However, the increasing …
transmission of sensor data among electronic control units. However, the increasing …